TimeSets for uncertainty visualisation
Salisu, Saminu, Xu, Kai 
ORCID: https://orcid.org/0000-0003-2242-5440, Wagstaff, Adrian, Biggs, Mike and Phillips, Graham
(2016)
TimeSets for uncertainty visualisation.
Computer Graphics and Visual Computing (CGVC) 2016.
In: EG UK Computer Graphics & Visual Computing 2016, 15-16 Sept 2016, Bournemouth, United Kingdom.
ISBN 9783038680222.
[Conference or Workshop Item]
(doi:10.2312/cgvc.20161291)
|
PDF
- Final accepted version (with author's formatting)
Download (1MB) | Preview |
Abstract
TimeSets consist of a timeline showing sequence of events displayed across a visualisation, while makings sense of sets relation among events in the timeline [NXWW15]. This study looked into extending TimeSets to accommodate Visualisation of trust and uncertainty as parts of its variables for events displayed across the timeline. The aim of the challenge is to build tools in the context of big data analytics that can be used to aid military operations through intelligence analytics and decision-making.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Salisu, S., Xu, K., Wagstaff, A., Biggs, M. and Phillips, G. (2016) 'TimeSets for Uncertainty Visualisation' in Computer Graphics and Visual Computing (CGVC), Eurographics Association, pp. 25-27. ISBN 978-3-03868-022-2, DOI: 10.2312/cgvc.20161291 |
| Research Areas: | A. > School of Science and Technology > Computer Science |
| Item ID: | 22111 |
| Notes on copyright: | The full text is the author's accepted manuscript version made available in this repository in accordance with the publisher's (Eurographics) self-archiving policy. The definitive version is available in the Eurographics Digital Library (http://diglib.eg.org/) at http://dx.doi.org/10.2312/cgvc.20161291 |
| Useful Links: | |
| Depositing User: | Kai Xu |
| Date Deposited: | 20 Jun 2017 08:29 |
| Last Modified: | 29 Nov 2022 21:35 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/22111 |
Actions (login required)
 |
View Item |
Statistics
Additional statistics are available via IRStats2.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)